A feature frequency analysis program has been written which tabulates features for groups of organisms and the uniqueness of each feature for each group. Since grouping of organisms can be based on any logic, the uniqueness of a feature for organisms for a specific disease may be determined. Ranking the features by their mean deviations measures their ability to efficiently partition the groups. We have developed an algorithm for displaying the level of redundancy of features. The programs aid the microbiologist in choosing the "best" set of features useful in identification by probabilities. Algorithms are being developed and tested for aiding in numerical taxonomy of feature by strain matrices too large to be analyzed by existing programs. Both segmentation and heuristic approaches are being investigated. Computer graphic algorithms are being tested to aid microbiologists in visualizing individual similarities as well as hierarchical groups memberships among strains.